Chief Marketing & Strategy Officer, MongoDB Inc.
Peder Ulander, MongoDB, and Mona Chadha, AWS | MongoDB.local NYC 2024
Peder Ulander, CMO of MongoDB, and Mona Chadha, director of category management at AWS, discuss the integration of MongoDB with Amazon Bedrock at MongoDB.local NYC. TheCUBE Research analyst Dave Vellante joins them to explore how this collaboration accelerates AI development and enables seamless integration of MongoDB with AWS' managed foundation models.
Get insights into what you might have missed at MongoDB.local NYC https://siliconangle.com/2024/05/07/m...
The discussion highlights MongoDB's involvement in AWS' Generative AI Competency Partners program and its new AI Applications Progra...
About Peder Ulander
At MongoDB.local NYC in May 2024, Ulander discussed the company's AI Applications Program and its integration with Amazon Bedrock. He stated that the program brings together a "rich ecosystem with validated reference designs" to help customers get started on AI journeys. Ulander noted that "generative AI is much more than just large language models" and involves multiple layers including infrastructure, orchestration, and security. He also highlighted MongoDB's involvement in AWS' Generative AI Competency Partners program, saying it "ensures customers have trusted, vetted solutions with high security standards." At MongoDB World in June 2022, Ulander discussed the company's acquisition of Aroki and the introduction of query-able encryption, which he described as enabling developers to build searchable capabilities into applications while maintaining security and privacy. He emphasized MongoDB's ability to operate across environments from on-premises to multi-cloud and edge, citing examples such as using Realm for connected cars. Ulander stated that "modernizing data architecture is essential" as other aspects of infrastructure have already transformed.
Transcript (27 segments)
H
Host0:10
Got a great conversation here. Peter Ulander is here, he's a CMO at MongoDB. He made all this happen, and it's, of course, with his team. And Monada, the director of category management at AWS. Great to see you guys. What's happening?
M
Monada0:23
Thanks for having us. Yeah, thanks guys. Both been on the Q before. Monada, what's happening in your world? Tell us about your role.
So yes, I head up all of our infrastructure ISVs. My team manages all of the partnerships for ISVs that fall into categories like security, networking, storage, database, data and analytics, AIML, generative AI, DevOps, CloudOps. Think of this as a team that manages partnerships for everything except for longtime partners, and really helping to get ISVs to integrate to AWS services and deliver those to our end customers or joint end customers.
H
Host1:23
It wasn't that long ago, was I wrong? You guys merged the APN and the ISV network, and that gives you way more scale and flywheel to use. Yeah, I mean, what we did was we merged our AWS Marketplace into the AWS Partner Network. So what that did was, MongoDB has been a seller on AWS Marketplace, and what that does is it provides all of the software and services that ISVs provide, merged into the AWS partner network.
We were basically describing this new strategy that Amazon Web Services has for communications, which is we always get the fire hose at re:Invent, and they were talking about basically more fire hoses throughout the year. So I saw Swami the other day, you know, on LinkedIn, he released some stuff. The Q announcement that we got briefed on last night. Part of Swami's was the gen competency launch, yes. That was part of his fire hose. Who explained what that is? And I'm dying to know what you think about it.
M
Monada2:43
Yeah, yeah, it's great. So first, let me explain the concept of what we mean by AWS partner competencies. What that essentially is, we found that our partners have differentiated skill sets and offer a variety of different solutions. Those partners can help customers with integrations into their applications. The competency spans different tools, infrastructure, and applications across different partners like SIs and ISVs. One of the key areas that we created a competency around is generative AI. As we were building out our generative AI services like Amazon Bedrock and Q and SageMaker, we wanted to ensure that customers had exposure to all the different partner integrations associated to that. As a result, we have a variety of different integrations across multiple competencies. We launched the generative AI competency back in 2023. The key thing about these competencies is that they're vetted, we have a high security bar, so customers have trust in any partner that is part of the competency.
H
Host4:26
So you're a trusted partner. What's your angle here?
P
Peder Ulander4:29
Yeah, no, I mean, it's exactly that. I think you heard Dave this morning in the keynote. He said especially in gen AI, 87% of executives know they need to get into gen AI but they don't know where to start. When you look at the ecosystem technologies that are out there, every week hundreds of new services or solutions are coming out. So how do I know this is going to work for me? How do I know these pieces are going to work together? That's such a critical component. When you think about AWS with now 275 competencies, the competency becomes that badge of trust, support, and knowledge that it is the right way to get started with these technologies working together. If anything, think back to the original days where it was nothing more than a certified partner and it was a stamp. This is taking that way further along because it comes with all of the tools, documentation, guarantees, APIs, and integrations that customers need. That integration is key; it's real engineering work.
H
Host5:41
Okay, and now you also announced that you're GA in Bedrock. What does that mean? What's specifically...
P
Peder Ulander5:49
Well, you'll speak better about Bedrock than I will, but I think at the end of the day, Bedrock is that orchestrational layer. You can almost call it an AI platform. You need a database, right? So MongoDB comes in. We sit with Bedrock. It enables developers to use the tools for building the apps that they want to use, knowing full well that they don't have to leave that console to come to our console to integrate MongoDB. We're part of the overall orchestration unit so they can move quickly.
H
Host6:30
I like the way Peter explained that because I think a lot of times AWS is misunderstood. People think LLMs equal AI, and we've applied it and it's just not that simple. Especially if you want to get real business value out of it, you need all these other frameworks and tools. People talk about guardrails — what does that mean? You need security, you need to make sure the LLM is not leaking data, etc. So what would you add to that about Bedrock?
M
Monada6:56
Yeah, you know, in terms of that integration, one of the key things we focus on is having the infrastructure available — the compute, the chipsets — with Amazon Bedrock in the middle layer, where again we want to give customers choice in terms of what type of foundational models they can use and integrate into their applications, and be able to readily use that in their real-world sort of applications. I think this is just the tip of the iceberg in terms of the integration work that we've been doing together with Bedrock. We're seeing a ton of customer feedback and desire to say, 'We need help getting started with generative AI, and this gets us in the right direction.'
H
Host7:52
And we saw the big announcement, I guess it was yesterday, about MAP. I mean, you're seeing a common thread here: customers want to have the easy button to get started. They want to have the guarantees that things are working together. The third frame of that is they want to know that it's going to be applicable to the use case or the business problem that they're trying to solve. We saw a huge opportunity in the fact that over the last year, we've been working across various industries — retail, finance, telco, etc. — helping them get started on that AI journey. We saw specific use cases, development patterns, architectural patterns, and technologies that were really critical in helping them get moving quickly. MAP brings together that rich ecosystem with validated reference designs based on the use cases they're trying to achieve, and the integrations into Bedrock and Q and everything else just makes them such a critical piece of that partnership.
P
Peder Ulander9:16
Oh yeah, definitely. And just to further emphasize the point, customers really need prescriptive guidance in terms of how to get started with AI. Everyone just thinks AI is about a chatbot — it is not. It is not. It's way more complicated than that. Having programs like MAP, and we were really excited to join MAP because again, we're giving customers more guidance in terms of here's how you get started, here are the use cases. One of the things that marries really well into MAP is also we've provided our customers with an AI use case explorer to again help them through all the different ways to leverage generative AI faster. So there are ideas in there and there are also packaged solutions, blueprints, and packaged solutions. The component of MAP is also the services packs, right? On one side, it could be an exploratory service to say what use cases are going to be the starting point, what's going to get me moving with the biggest impact. That level of services is really critical. Or there's another one: you've decided on the use case, you want this is how we bring those blueprints, reference architectures, and integrations forward so that you can move from ideation to market as fast as possible.
H
Host10:48
And you mentioned Marketplace before. That's been huge. I think it's really a differentiator for AWS and its partners. How have you leveraged Marketplace?
P
Peder Ulander11:10
Buying compute, network, and storage in Amazon services, Amazon has become kind of this hub for all types of third-party ecosystems to solve business needs. It becomes that single point of presence for billing and operations for a lot of companies. What this does is it removes the complexity of saying not only do we know that MongoDB Atlas and AWS work together, but now you can ensure you have one bill, one engagement, one license. It basically creates an easy wrapper so that customers can transact with these solutions together.
H
Host11:42
I know we're up against the clock. You had something to add.
M
Monada11:46
Well, I know I'm just going to add to that. I want to give a lot of kudos here because MongoDB has been one of our partners that really adopted a lot of our features, ranging from things like documentation around HIPAA, SOC 2, FedRAMP. That is a huge value to our end customers. I have to say MongoDB does a really amazing job of adopting the buyer features and capabilities so that it makes it easier for the end customers to procure through the marketplace. They get the added benefit of speed of procurement acceleration, and the end customer gets everything they need all in one spot, however they want to transact. It's a real benefit to our end customers.
H
Host12:44
And MongoDB also didn't resist cloud. Knew you had to go cloud native. Atlas was a game changer for the company and your customers. My last question — I know we're up against the clock — I want to talk about gen AI. The real interesting harder use cases, there's ROI today, don't get me wrong, but the big value is still not there. The big chew, there are examples you guys gave this morning but they're not at scale yet. So what are you guys seeing and what's your expectation for gen AI adoption beyond some of those lighter weight applications?
M
Monada13:31
Yeah, I think it's still very early. Customers like we just said need help getting started. So what I anticipate is that more and more industries are going to leverage generative AI in very unique ways. These are industries across financial services, healthcare, retail. It's going to go beyond the chatbot. We're already seeing very innovative ways in which customers are using gen AI, for instance with your teams, how do you get your teams to become more efficient? This is like psychology, right? So you're starting to see very interesting approaches, but there's going to be more to come. I think the future really is in getting the data right. What you'll see is just better models, better collection of data, and weeding out all of the data that's not good, which would prevent a model from coming out with a good outcome. I think that's going to get better. I think overall technology is going to get better. This is why AWS has invested in chipsets and our technology, so that models are just going to get faster, better, more reliable, more trustworthy. As that happens, your compute power needs will increase.
H
Host15:10
I know you got to go, but we want to give you the last word on the relationship and also MongoDB local and what's next.
P
Peder Ulander15:19
This is the first stop across 23 cities around the globe. We're bringing gen AI to the world, helping developers get started quickly. We're really excited about being here in New York. Thank you again for joining us. The ability for us to get this in the hands of the developers has been absolutely key. To the point of where we are in the gen AI movement, it's early. It's about enablement, it's about exploration, it's about helping customers understand where to get started. There's no better way to do that than leverage these local series to get your developers in front of the experts with all of the partner ecosystem tools and technologies that you need to move forward. That's why we're really happy about this program.
H
Host15:59
Happy December. We'll go out and we keynote, so it brings the execs out into the field where our customers are. We're not allowed to do the same ones we did last year, so we've got to go meet new folks every time. This year I have a tour in India and Southeast Asia, so it'll be good.
P
Peder Ulander16:27
Oh, fantastic.
H
Host16:29
All right, thanks you guys.
M
Monada16:30
Thank you so much.
H
Host16:31
Keep watching. We'll be right back after this short break. MongoDB local, live from New York City, watching the Q.